A FPGA-based qpsk neural network demodulator and its control method
A neural network and convolutional neural network technology, applied in the field of FPGA-based QPSK neural network demodulator and its control, can solve the problems of upgrade and improvement, poor robustness of the demodulator, etc., to improve adaptability and structural stability The effect of high and low computational complexity
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
Method used
Image
Examples
Embodiment 1
[0039] See figure 1 , figure 1 A schematic structural diagram of an FPGA-based QPSK neural network demodulator provided by an embodiment of the present invention.
[0040] The embodiment of the present invention provides a kind of FPGA-based QPSK neural network demodulator, comprising:
[0041] Clock and reset module, used to send clock signal and reset signal;
[0042] AD sampling module, used for sampling the signal to be demodulated to obtain sampling data;
[0043] The input buffer module is used for receiving and buffering sampled data, and performing clock domain conversion on the sampled data;
[0044] A phase mutation detection module, configured to detect a relative phase change in the sampled data after clock domain conversion, and output phase mutation information;
[0045] The constellation rotation and data flipping module is used to receive and process phase mutation information to form baseband data;
[0046] The synchronous output module is used for synchr...
PUM
Login to View More Abstract
Description
Claims
Application Information
Login to View More 


